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PRINTED FROM the OXFORD RESEARCH ENCYCLOPEDIA, BUSINESS AND MANAGEMENT (oxfordre.com/business). (c) Oxford University Press USA, 2019. All Rights Reserved. Personal use only; commercial use is strictly prohibited (for details see Privacy Policy and Legal Notice).

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date: 15 September 2019

Abusive Supervision

Summary and Keywords

In recent years scholars of abusive supervision have expanded the scope of outcomes examined and have advanced new psychological and social processes to account for these and other outcomes. Besides the commonly used relational theories such as justice theory and social exchange theory, recent studies have more frequently drawn from theories about emotion to describe how abusive supervision influences the behavior, attitudes, and well-being of both the victims and the perpetrators. In addition, an increasing number of studies have examined the antecedents of abusive supervision. The studied antecedents include personality, behavioral, and situational characteristics of the supervisors and/or the subordinates. Studies have reported how characteristics of the supervisor and that of the focal victim interact to determining abuse frequency. Formerly postulated outcomes of abusive supervision (e.g., subordinate performance) have also been identified as antecedents of abusive supervision. This points to a need to model dynamic and mutually reciprocal processes between leader abusive behavior and follower responses with longitudinal data. Moreover, extending prior research that has exclusively focused on the victim’s perspective, scholars have started to take the supervisor’s perspective and the lens of third-parties, such as victims’ coworkers, to understand the broad impact of abusive supervision. Finally, a small number of studies have started to model abusive supervision as a multilevel phenomenon. These studies have examined a group aggregated measure of abusive supervision, examining its influence as an antecedent of individual level outcomes and as a moderator of relationships between individuals’ experiences of abusive supervision and personal outcomes. More research could be devoted to establishing the causal effects of abusive supervision and to developing organizational interventions to reduce abusive supervision.

A seminal article by Tepper (2000) initiated a large body of research on the topic of abusive supervision. Abusive supervision is defined as “subordinates’ perceptions of the extent to which supervisors engage in the sustained display of hostile verbal and nonverbal behaviors, excluding physical contact” (p. 178). According to a recent review of abusive supervision (Kermond & Schaubroeck, 2015), by 2013 over 100 journal articles had been published on the topic. The high volume of published work has continued during the last five years.

Abusive supervision is viewed in the context of supervisor–subordinate relationships in the workplace and includes such behaviors as ridiculing subordinates, taking personal credit for their work, and invading their privacy. Within the aforementioned definition of abusive supervision, its “sustained” nature means that abusive supervision is not seen to occur if the follower experienced only one or two episodes of hostile behavior. While abusive supervision may certainly be distressful and trigger harmful health outcomes, it does not rise to the level of physical abuse. Abusive supervision also hinges on the subordinate’s judgment of whether the behavior constitutes abuse by being both hostile and sustained. This also suggests that two people may have very different perceptions of the same behavior and may not agree on the presence of abusive supervision. With a few exceptions in which authors manipulated a specific form of abusive behavior in a laboratory setting (Porath & Erez, 2007; Rodgers, Sauer, & Proell, 2013), researchers have measured abusive supervision using subordinates’ self-reports of being abused by their leaders. The subjective nature of its operationalization has raised a concern that research captures only subordinates’ appraisals of abusive supervision but not the actual leader behaviors (Chan & McAllister, 2014). The exclusive focus on subordinates’ perceptions, albeit consistent with the conceptualization (Tepper, 2000), may lead to overestimates of the causal relationship between abusive supervision and follower self-reported attitudes and psychological states. It is thus valuable to examine abusive supervision from others’ perspectives besides through the lens of the targeted subordinates. For example, recent work has examined abusive supervision from the perspective of the supervisors (Barnes, Lucianetti, Bhave, & Christian, 2015; Li, Wang, Yang, & Liu, 2016) and from the perspective of the third parties (Mitchell, Vogel, & Folger, 2015; Peng, Schaubroeck, & Li, 2014).

As compared with a list of similar constructs (Kermond & Schaubroeck, 2015, Table 1), what distinguishes abusive supervision is that it relates to behavior rather than constituting a trait (cf. aversive leadership, petty tyranny), is sustained (cf. supervisor incivility, verbal aggression), and is directed toward a particular subordinate (cf. aversive leadership, petty tyranny, supervisor bullying). In a review, Tepper (2007) noted that supervisor social undermining is very similar to abusive supervision, the difference being that perceived intention to harm the focal subordinate is included in defining social undermining but not abusive supervision.

Abusive Supervision Consequences

Much of the research on the consequences of abusive supervision is concentrated on the victim’s responses and reactions, including behaviors, attitudes, and well-being.

Family

Abusive supervision appears to have spillover effects outside of the work realm. The Mackey et al. (2017) meta-analysis shows a low to moderate-size positive relationship between perceptions of abusive supervision and work-to-family conflict (ρ‎ = .35, k = 6, N = 1,527) (Mackey et al., 2017; Tepper, 2000). In a study on the connection between electronic communication during non-work time and work-to-non-work conflict, Butts, Becker, and Boswell (2015) found that abusive supervision strengthened the relationship through increasing anger and conflict. Employees who have abusive supervisors are more likely to bring negative work emotions home, acting aggressively toward their family members or domestic partners (Hoobler & Brass, 2006). Additionally, abused subordinates may experience greater relationship tension and lower family satisfaction (Carlson, Ferguson, Perrewé, & Whitten, 2011).

Abusive Supervision Mechanisms

Scholars have sought to understand what might explain the relationship of abusive supervision to negative outcomes. Perhaps the most popular approaches have been relational theories, such as social exchange, and emotion-based theories, such as the emotion response theory.

Relational Theories

We refer to relational theories as those that seek to explain how abusive supervision impacts the relationship between a subordinate and their supervisor or organization. For example, social exchange theory claims that relationships are grounded in reciprocity norms, which govern employees’ assessments of the costs and benefits of relationships (Blau, 1964).

Social Standing and Esteem

Exchange perspectives have been applied to explain how abusive supervision promotes deviant behavior or decreases helping behaviors (Peng et al., 2014). Separate from exchange are relational theories of abusive supervision that emphasize how it undermines employees’ sense of social status among other employees. Tyler and Blader’s (2000) group engagement model proposes that mistreatment by the leader reduces social status among peers, which in turn leads to lower motivation to behave in ways that benefit the group (“group promoting” behaviors) and weakens motivational constraints on behaviors that are antagonistic to well-being or effectiveness (“group limiting” behaviors), such as deviant or counterproductive behaviors. For example, Schaubroeck, Peng, and Hannah (2016) found that a relatively high (compared with group peers) level of abusive supervision (i.e., relative abusive supervision) influenced performance and other outcomes through lower perceived peer respect. The relationships were stronger among groups with higher levels of group potency. Some researchers have also suggested that abuse victims’ diminished self-confidence contributes to their deviant behaviors (Nandkeolyar, Shaffer, Li, Ekkirala, & Bagger, 2014). For example, Vogel and Mitchell (2017) found that state self-esteem mediated the relationship between abusive supervision and deviant behavior.

Social Exchange

Leader–member exchange (LMX), an indicator of trust and loyalty perceived in the supervisor–subordinate relationship (Scandura & Graen, 1984), has been utilized to operationalize social exchange quality in some studies of abusive supervision. For example, Xu, Huang, Lam, and Miao (2012) found that LMX quality mediated the relationship between abusive supervision and organizational citizenship behaviors. Peng et al. (2014) found that LMX, and, separately, affect-based trust in co-workers, mediated the relationship of abusive supervision on task performance and helping behaviors. However, none of these studies conclusively supported a particular causal order of abusive supervision and LMX. Recent work has also indicated that this relationship may be reversed, such that poor LMX triggers higher levels of abusive supervision (Pan & Lin, 2018).

Attributing Blame to the Organization

In some cases, employees with abusive supervisors may retaliate against the organization. Employees tend to view their leaders as representing the organization (Eisenberger et al., 2010), and given the power asymmetry with leaders, subordinates may be more fearful of acting out against them. Shoss, Eisenberger, Restubog, and Zagenczyk (2013) supported this idea in a study examining perceived organizational support as a mediator of the relationship between abusive supervision and organization-directed citizenship behaviors. Tepper et al. (2008) found that victims of abusive supervision reported lower organizational commitment than non-victims. They attributed this to victims’ blaming of the organization for their abuse. Yu et al. (2016) similarly found that the link between abused subordinates and job performance was mediated by affective organizational commitment.

Emotions and Self-Regulation

Recent theoretical work has examined the effects of abusive supervision through the lens of emotional process theory (Oh & Farh, 2017). In their article, Oh and Farh (2017) argued that abusive supervision elicits feelings of anger, fear, and sadness in victims that then affects their behaviors. Emotional states are associated with particular action tendencies (Frijda, Kuipers, & TerSchure, 1989). Empirical work broadly supports that emotional states at least partially explain relationships between abusive supervision and victim behaviors. For example, higher abusive supervision is associated with higher levels of fear, anger, and anxiety (Mayer et al., 2012; Rafferty et al., 2010; Tepper et al., 2009), which in turn precipitates behavioral outcomes such as deviance. These emotional states can also reinforce the abusive behavior, creating a cycle of abuse (Simon, Hurst, Kelley, & Judge, 2015).

Abusive supervision is also seen to drain emotional and psychological resources, which in turn produces destructive behaviors. For example, studies have reported that victims of abusive supervision were more prone to emotional exhaustion, which in turn was associated with lower levels of knowledge sharing with the team or organization, more employee silence, and reduced creativity (Lee et al., 2018; Xu et al., 2015; Han et al., 2017). Abused subordinates may suffer from a reduced ability to self-regulate their emotions, which diminishes impulse control (Lian et al., 2014; Thau & Mitchell, 2010). Based on a longitudinal study, Liang et al. (2018) reported that rumination in the aftermath of abusive supervision explains its relationship with physical health.

Abusive Supervision Predictors

In recent years there has been a heightened focus on identifying antecedents of abusive supervision. The studied antecedents are primarily characteristics of supervisors and characteristics of the subordinates. Future research may expand this stream to study other overlooked supervisor or subordinate characteristics as antecedents of abusive supervision. In addition, researchers may examine how contexts and situations (e.g., time and performance pressure, resource constraints, and organizational norms) trigger supervisory abuse or exacerbate the propensity for a certain type of stimulus (e.g., subordinate deviance) to instigate abuse.

Supervisor Characteristics

Supervisor Traits

A small number of studies have examined supervisor traits as antecedents of abusive supervision. Supervisor Machiavellianism, a behavioral tendency to manipulate and exploit others to maximize self-interests (Christie & Geis, 1970), predicted abusive supervision (Kiazad, Restubog, Zagenczyk, Kiewitz, & Tang, 2010; Wisse & Sleebos, 2016). Kiazad et al. further showed that an authoritarian leadership style, defined as “leader’s behaviour that asserts absolute authority and control over subordinates and demands unquestionable obedience from subordinates” (Cheng, Chou, Wu, Huang, & Farh, 2004, p. 91), explained the positive association between supervisor Machiavellianism and abusive supervision. A study by Wisse and Sleebos (2016) indicated that supervisors’ perceived position of power exacerbated the positive relationship between Machiavellianism and their display of abusive behavior in the work units. While previous research suggests that subordinate trait negative affect precipitates abusive supervision, Pan and Lin (2018) also found that supervisors’ trait negative affect was positively associated with subordinates’ reports of abuse.

Supervisor Experience

Drawing on displaced aggression theory (Miller, Pedersen, Earleywine, & Pollock, 2003), studies have proposed and found that leaders who themselves have experienced abuse or unfair treatment by their supervisors and/or the organization are more likely to displace their aggression onto their subordinates. For example, studies have shown that the extent to which higher-level managers engage in abusive supervision is positively associated with the abusive behavior displayed by the lower-level managers (Liu et al., 2012; Mawritz et al., 2012). This phenomenon is also known as a “trickle-down” (or “cascading”) effect. Supervisors who experience procedural injustice (Tepper, Duffy, Henle, & Lambert, 2006), interactional injustice (Hoobler & Hu, 2013; Rafferty et al., 2010), or psychological contract violations (Hoobler & Brass, 2006; Rafferty et al., 2010) have also been found to engage in abusive supervision.

Studies have also examined the interaction between supervisor self-regulatory capabilities (e.g., self-control) and the resource-depleting situational factors on abusive supervision. Yam et al. (2016), for example, showed that engaging in surface acting depleted state self-control resources and, in turn, led to elevated abusive behavior, but only among supervisors with relatively low trait self-control. Similarly, across two independent field studies, Lam et al. (2017) found that supervisors’ experience of emotional exhaustion was positively associated with abusive supervision when both subordinate performance and supervisors’ self-monitoring were relatively low. Kiewitz et al. (2012) reported that supervisors’ childhood experiences of family undermining (e.g., parent insults) were associated with a proneness to exhibiting abusive supervisory behaviors among those who had limited control over their impulses.

Subordinate Characteristics

Subordinate Traits

The victim precipitation model (Elias, 1986) suggests that targets of abuse often possess certain traits or characteristics that directly or indirectly make them more likely to be mistreated by others. A subordinate trait that is often examined is negative affectivity, a tendency to experience negative mood states such as distressed, angry, jittery, or upset (Watson, Clark, & Tellegen, 1988). Subordinates with higher negative affectivity report higher levels of abusive supervision (e.g., Hoobler & Hu, 2013; Tepper et al., 2006). Studies have also shown a positive association between psychological entitlement and abusive supervision (Harvey, Harris, Gillis, & Martinko, 2014; Mackey et al., 2016). Other subordinate traits that have been linked to abusive supervision include a hostile attribution style (i.e., a tendency to attribute negative events to external and stable causes) (Martinko, Harvey, Sikora, & Douglas, 2011), neuroticism (Wang, Harms, & Mackey, 2015), lower levels of core self-evaluation (Kluemper et al., 2018), and lower organization-based self-esteem (Kiazad et al., 2010). It is unclear, however, whether such findings reflect the tendency of individuals with certain traits to provoke abuse or whether individuals with these traits tend to interpret their interactions with the leader in a negative way.

Subordinate Deviance

Abusive supervision is also found to be provoked by subordinates’ acts of workplace deviance. In a two-wave longitudinal study, Lian et al. (2014) reported a time-lagged positive relationship between organizational deviance and abusive supervision. More recently, Mawritz, Greenbaum, Butts, and Graham (2017) found across two field samples that subordinates’ supervisor-directed deviance was positively related to their subsequent reports of supervisory abuse and that supervisor self-regulation impairment explained this relationship. In addition, the authors found the indirect positive effect of subordinate deviance on abusive supervision was stronger among supervisors who had a high bottom-line mentality and among those who perceived their subordinates exhibited high levels of job performance.

Methodological Issues

Kermond and Schaubroeck’s (2015) review identified several methodological issues in the abusive supervision literature. These included construct proliferation (i.e., a variety of constructs that are similar to abusive supervision), cross-sectional research design that is subject to common method bias, and inadequate model specification in which studies often test a single mediator. We found that, generally speaking, these issues have persisted in the abusive supervision literature, although a number of studies have utilized either longitudinal or time-lagged designs and have included different sources to measure predictors or outcomes (e.g., Barnes et al., 2015; Liang et al., 2018; Schaubroeck et al., 2016; Simon et al., 2015). In this review, we primarily focus on the magnitude of the abusive supervision effect.

Potentially Inflated Abusive Supervision Effect

To date, abusive supervision research has primarily relied on between-person correlational designs in which self-reports on abusive supervision relate to an outcome variable of interest. While a design in which the outcome variable is rated by a different source and/or measured at a later point of time would alleviate concerns of common method bias, the observed abusive supervision effect may still be inflated owing to omitted variables that confound the effect. For example, Mackey et al. (2017) reported a meta-analytic correlation of .41 between abusive supervision and counterproductive work behavior (CWB; k = 7, N = 1,715). Yet this relationship may not represent the true causal influence of abusive supervision on CWB. This is because, as noted above, the abusive supervision–CWB relationship may be at least partly determined by unmeasured variables such as hostile personality. Subordinates with high trait hostility, for example, may tend to interpret leader behaviors as hostile and abusive (Lerner & Keltner, 2001), and meanwhile they tend to express their hostility by engaging in CWB. As a result, the observed positive effect of abusive supervision on counterproductive behavior may be spurious due to the omission of trait hostility.

One remedy to this issue is to use a longitudinal design in which abusive supervision and the focal outcome are measured at multiple points in time. Using the abusive supervision–CWB relationship as an example, one could test a cross-lagged model that controls for the prior level of counterproductive behavior and thus reduces the concerns for unmeasured confounding variables. Simon et al. (2015) illustrated this approach by examining a time-lagged relationship between abusive supervision and deviance directed toward the supervisor while controlling for the prior level of deviance. Not surprisingly, the reported effect size (B = .11, p < .01, one-tailed) was relatively smaller than those typically reported in the literature. Another example can be seen in the study by Liang et al. (2018). The authors tested a cross-lagged model of the relationships between abusive supervision and subordinate health outcomes. With a longitudinal design, one may examine a two-level model that differentiates within-person from between-person effects. In this way, the within-person effect would suggest that any intrapersonal change in experience of abusive supervision is associated with change in the focal outcome. The within-person effect therefore would provide a better approximation of the causal effect of abusive supervision by modeling intrapersonal change. For instance, Barnes et al. (2015) showed a positive within-person relationship between abusive supervision and next-day work engagement in an experience-sampling study.

Promising Future Directions

Third-Party Reactions to Abusive Supervision

The deontic justice perspective proposes that third-party observers may experience feelings of anger in responding to another person’s injustice experience and exhibit behavioral tendencies to restore justice such as punishing the perpetrator or helping the victim (Folger & Cropanzano, 2001; Turillo, Folger, Lavelle, Umphress, & Gee, 2002). A third-party observer refers to an individual who witnesses another individual’s mistreatment or learns about the unfair treatment indirectly through conversations with the victim or others. Drawing from this perspective, experimental research has examined how third-party observers react to leader abusive behaviors as manipulated in scenarios (Skarlicki & Rupp, 2010; Umphress et al., 2013, Study 1; Shao, Li, & Mawritz, 2018, Study 1). In an experimental study with 186 managers, Skarlicki and Rupp (2010) showed that third-party observers of leader abuse reported higher retribution tendencies such as reporting and reprimanding the supervisors’ misbehavior. Their retribution tendencies were also stronger among participants with higher moral identity and those who were primed with an experiential (vs. rational) informational processing frame. Similarly, Umphress et al. (2013) showed across three experimental studies that third-party observers displayed anger toward the abusive supervisor and they reported an intention to punish the supervisor, especially when the supervisor intended to inflict injustice on the targeted follower. In two studies (Studies 2 and 3), Umphress et al. (2013) created a realistic experience in which the participants believed that an actual interaction between a supervisor and a subordinate had occurred.

Scholars have also examined the third-party experience of abusive supervision in field settings (Harris, Harvey, Harris, & Cast, 2013; Jiang, Gu, & Tang, 2017; Mitchell et al., 2015; Shao et al., 2018, Study 2; Peng et al., 2014). These studies have examined how employee outcomes are influenced by peer abusive supervision. Peer abusive supervision refers to the extent to which other co-workers are abused by the leader (Peng et al., 2014). For example, Mitchell et al. (2015) found that employees who witnessed or were aware of leader abuse toward other co-workers reported higher levels of anger and accordingly deviant behavior toward the supervisor. Jiang et al. (2017) found that peer abusive supervision was negatively related to creative self-efficacy, which was in turn positively related to creative performance. Compared with own abusive supervision, the unfavorable influence of peer abusive supervision in their study was significantly weaker. While peer abusive supervision was linked to higher deviance and lower creative performance, Peng et al. (2014) reported no relationship between peer abusive supervision and job performance (or helping behavior) after controlling for one’s own abusive supervision. Finally, across two field studies and one experimental study, Shao et al. (2018) similarly reported a nonsignificant relationship between peer abusive supervision and performance effort. Interestingly, the authors found that among individuals with a relatively high trait prevention focus, peer abusive supervision had a positive effect on effort. Their finding thus revealed a self-protection motive whereby employees may invest more effort to avoid being abused by the leader.

In addition, research has found an interaction between own and peer abusive supervision on employee outcomes (Harris et al., 2013; Jiang et al., 2017; Peng et al., 2014). Harris et al. (2013) found that abused employees were more likely to abuse their co-workers when peer abusive supervision was low (vs. high). Own abusive supervision, however, was more negatively associated with perceived organizational support when peer abusive supervision was higher. Drawing from social exchange theory, Peng et al. (2014) proposed and found that peer abusive supervision moderated the relationship between own abusive supervision and employees’ perceived exchange relationships with the leader and, separately, with their peers. When peer abusive supervision was high, employees perceived a lower quality of exchange relationships regardless of the extent to which they were personally abused. The perceived social exchange relationships, in turn, explained the interaction effect on task performance and helping behavior. In line with the findings reported by Peng et al., Jiang et al. (2017) found that own abusive supervision had a negative influence on creative self-efficacy only when peer abusive supervision was low. They attributed such an interactive effect to the social comparison triggered by being singled out for abuse, and they found indirect support for this theorizing by showing that social comparison orientation moderated the aforementioned two-way interaction.

To summarize, research has emerged to understand the third-party observer’s experience of abusive supervision. The influence of peer abusive supervision on employee outcomes, however, remains relatively unexplored, particularly in field settings. Compared with the pervasive influence of own abusive supervision (Mackey et al., 2017), peer abusive supervision seems to have a less negative impact on the observers’ outcomes. Peer abusive supervision may even have the potential to promote better performance owing to the self-protective motive (Shao et al., 2018). Nevertheless, peer abusive supervision may create a negative social environment that fuels mistrust and hinders cooperation (Peng et al., 2014). We thus encourage research that examines a variety of employee and organizational outcomes to better gauge the impact of the vicarious experience of leader abuse. For example, studies may examine how abusive supervision of co-workers affects observers’ engaging in either prosocial behavior (e.g., taking initiative) or pro-self behavior (e.g., political behavior). In addition, research may compare different theoretical perspectives (e.g., social comparison, social exchange, social learning, deontic justice) in explaining the effect of peer abusive supervision. Considering alternative theoretical perspectives may be particularly fruitful to understand the interaction effect between own and peer abusive supervision on employee psychological states and behavior.

Multilevel Research

Tepper (2007) noted that “abusive supervision is a multilevel phenomenon and the field needs to move beyond individual-level research” (p. 281). Responding to this call, studies have examined the influence of abusive supervision at the work group level (Farh & Chen, 2014; Hannah et al., 2013; Rousseau & Aubé, 2018). By surveying a sample of 2,572 U.S. Army personnel deployed in Iraq, Hannah et al. (2013) found that the mean level of abusive supervision reported by the soldiers within the same squad (group abusive supervision, hereafter) had a negative influence on soldiers’ moral courage and identification with army values. The authors examined the influence of group abusive supervision in a two-level model whereby they controlled for individual-level abusive supervision. They also found a cross-level interaction between group and individual abusive supervision on courage and identification. Specifically, high levels of courage and identification were found among soldiers who were not personally abused by the leader nor had their squads reported supervisory abuse. Through moral courage and values identification, abusive supervision indirectly influenced unethical behaviors (e.g., mistreating noncombatants). In both a field study and an experimental study, Farh and Chen (2014) showed that group abusive supervision had a positive effect on relationship conflict at the team level, which negatively related to employee voice and in-role performance measured at the individual level. Consistent with Hannah et al. (2013), Farh and Chen reported a similar pattern of cross-level interaction between group and individual abusive supervision on individuals’ perceived organization-based self-esteem. Moreover, Rousseau and Aubé (2018) proposed and found a negative relationship between work group abusive supervision and team innovation as mediated by team proactive behavior. Finally, in a study of relative abusive supervision (i.e., abusive supervision centered by its group mean), Schaubroeck et al. (2016) found that group potency moderated the mediated effect through peer respect on performance and organizational commitment, as well as on turnover intentions.

The studies have primarily focused on the main effect of group abusive supervision on individual and/or group outcomes (see exceptions by Farh & Chen, 2014; Hannah et al., 2013). Future research might explore the idea that group abusive supervision serves as a social context that shapes individuals’ interpretations of their own treatment by the leader and/or their work experience in general. A high level of group abusive supervision may create a fearful environment in which individuals are less likely to trust others including their peers. Consequently, individuals may be prone to interpret their interactions with co-workers as hostile and respond with destructive behaviors. Alternatively, the shared experience of leader abuse may serve to unite the group members, leading to more supportive behaviors among them. Future research may also attend to the variability of leader abuse within the work units. Ogunfowora (2013) showed that variation in abusive supervision within the work unit was associated with employees’ unfavorable attitudes toward their leader, the job, and the organization. Yet when and how such an effect exists is unclear. Moreover, researchers may test a multilevel model that takes into consideration the abusive behavior of the higher-level leaders. Not only may higher-level leaders influence employee attitudes and outcomes indirectly through a trickle-down effect (Liu et al., 2012; Mawritz et al., 2012), the abusive supervision exhibited by the higher-level leaders may also strengthen or weaken the influences of the lower-level leaders’ abuse on employee outcomes, as seen in research on ethical leadership (Schaubroeck et al., 2012). Finally, as noted earlier, we encourage multilevel research that models both within-person and between-person effects of abusive supervision using longitudinal study designs.

The Reciprocal Relationship Between Abusive Supervision and Outcomes

Earlier research has primarily focused on the influence of abusive supervision on subordinate behavior (see review by Tepper, 2007). Recent work, as noted earlier, shows an increasing interest in proposing and testing subordinate outcomes (e.g., performance) as a predictor of abusive supervision (Lam et al., 2017; Liang et al., 2016; Walter et al., 2015). These suggest a possible reciprocal relationship between abusive supervision and employee outcomes. In a six-wave longitudinal study, Simon et al. (2015) provided indirect evidence for this reciprocal relationship. They found that employees’ deviance directed toward their supervisors was positively associated with their reports of abusive supervision one month later. In a separate model, they showed a positive time-lagged relationship between abusive supervision and supervisor-directed deviance. In addition, Kiewitz, Restubog, Shoss, Garcia, and Tang (2016, Study 3) tested and found a reciprocal relationship between abusive supervision and employee silence. Employee silence “refers to the withholding of potentially important input or to instances when an employee fails to share what is on his or her mind” (Morrison, 2014, p. 174). Abusive supervision reported at Time 1 was positively associated with a subsequent measure of employee silence, which, in turn, had a time-lagged association with abusive supervision measured at Time 3.

This reciprocal relationship raises an important concern on the adequacy of the research models that have largely focused on abusive supervision as either a predictor or an outcome. Focusing on one side of the story represents an incomplete picture of the relationship between abusive supervision and employee outcomes, and it may contribute to an inflated estimate of the relationship in cross-sectional studies. To fully model this reciprocal relationship, longitudinal data analytical techniques may be used to model change in abusive supervision and change in employee outcomes over time. In particular, the recent developments in latent growth modeling and latent change score modeling (see review by McArdle, 2009) may be valuable to help model the reciprocal relationship more precisely. For example, researchers may use a latent change score model to specify a dynamic and reciprocal relationship between change in abusive supervision and change in employee outcomes. In such a model, the change in leader abuse is linked to the subsequent change in an employee outcome and the change in the outcome is also linked to subsequent change in abusive supervision (Liao, Peng, Li, Schaubroeck, & Liu, 2016). The use of longitudinal designs in conjunction with refined statistical techniques could aid researchers in developing a more comprehensive understanding of how antecedents of abusive supervision are related to its consequences.

Conclusion

In recent years abusive supervision research has continued to flourish. Our review identified a number of promising empirical trends and theoretical advances. A focus on self-regulatory processes has emerged, and there has been greater attention to mediating emotional states, supervisor and subordinate precipitating characteristics, multilevel models, and third-party processes. There have also been interesting empirical advances that tested alternative causal orders and reciprocal relationships using longitudinal designs, and a quasi-experiment suggesting that training can reduce abusive supervision. Although the research is moving in promising directions, more effort could be devoted to establishing a causal process model of abusive supervision. This would in turn provide a foundation developing organizational interventions that prevent leader abusive behavior.

Ogunfowora, B. (2013). When the abuse is unevenly distributed: The effects of abusive supervision variability on work attitudes and behaviours. Journal of Organizational Behaviour, 34, 1105–1123.Find this resource:

Wang, G., Harms, P. D., & Mackey, J. D. (2015). Does it take two to tangle? Subordinates’ perceptions of and reactions to abusive supervision. Journal of Business Ethics, 131, 487–503.Find this resource:

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